Primary Analysis On The Characteristics Of Postganglionic Inferior Cardiac Sympathetic Nerve Activity And On The Mode Of Regulating Heart Rate

While exploring the physiological mechanisms responsible for autonomic nervous system regulating the cardiovascular functions, discussing the characteristics of autonomic nervous activity is very useful for it can uncover the modes of autonomic nervous activity and traits of autonomic nervous activity in different modes,and it can help to understand the autonomic nervous activity on the view of electrophysiology .On this basis, combining the cardiovascular states with characteristics of aotonomitic nervous activity can search the relationship between autonomic nervous activity and heart rate variability(HRV), discover the rules with which autonomic nervous system regulate the cardiovascular system,use the information supplying by autonomic nervous activity efficiently. What's more,it can supply the biophysical and electrophysiological proof to develop the new types of pacemaker and other heart anabiosis devices.In the analysis of statistics analysis and spetral analysis is not powerful enough to get the information contained in the nervous activity. With the development of nonlinear analysis method,it has displayed more and more advantages for it can extract information that other usual methods can't . So we took primary analysis on the characteristics of postganglionic inferior cardiac sympathetic nerve activity (ICSNA) and on the mode of regulating heart rate with differentmethods especially nonlinear analysis method. Through doing this, we can grasp the rules of ICSNA and extract the coupling relationship between ICSNA and HRV.Taking ICSNA as a window,discuss the way on which autonomic nervous system regulate the cardiovascular system in detail.Taking cats as experiment animals, we have constructed animal models for ICSNA recording while animals were anaesthetized by intraperitoneal injection of nembutalum with vagus nerve and baro-receptor remaining intact. Using biological function experiment system, we collected ICSNA, ECG and BP simultaneously.First, with autoregressive model method, Chebyshev digital filter and cluster analysis based on pooled t-test, synchronized inferior cardiac sympathetic nerve activity (SICSNA) was got and four characteristics exponents of SICSNA were extracted including Peak_interval, Peak_area, Peakwidth and Peakheight; With interpolating and resampling, Peak Interval Series(PIS) was got through Peak interval; R apex was detected from ECG and R-R Interval(RRI) was calculated. With interpolating and resampling, Heart Rate Variability(HRV) was obtained from RRI; According to RRI and SICSNA, RR-related Discharge(RRD) reflecting coupling between RRI and SICSNA was obtained; With high-pass filter,band-pass filter and low-pass filter, Cardiac-related discharge was extracted from SICSNA and its peak was detected;With it and R apex, Peak-R Phase (PRP) and Peak-Peak interval (PPI) were got to quantify the coupling between SICSNA and HRV.We have adopted statistic analysis, chaos analysis, fractal analysis and complexity analysis to analyze the SICSNA, its four characteristics, HRV and PIS.With statistic method, SICSNA and its four characteristics were analyzed . The results show that (1)SICSNA has three levels of scale:largest scale in harmony with respiratory known as group discharge,middle scale in terms of heart beat known as cardiac-related discharge and the smallest scaleof cluster discharge;(2)In SICSNA, there exists three frequency bands, including band below 1 Hz, band near heart rate and band between 6 Hz and 20 Hz; Peak-interval has multi-modal distribution, whereas other characteristics have single-modal distributions, and distributions of Peakarea and Peak height are like gamma distribution.Applying Lyapunov exponent (LE) analysis and correlation dimension(CD) analysis, chaos analysis was carried on upon HRV and PIS. The results show that (1) The deterministic chaos lies in the HRV and PIS;(2) The largest LE of HRV is larger than that of PIS, and except in experiment one and three, the CD of HRV is smaller than that of PIS.Applying detrended fluctuation analysis (DFA), SICSNA and its four characteristics were analyzed fractally. The results show that (1) There exists fractal characteristics and long term correlation in the Peakinterval, Peakheight and Peak_area;(2) Long term correlation doesn't lie in Peak_width.With approximation entropy (ApEn) and corrected conditional entropy (CCE), complexity analysis was carried on upon the PIS. The result shows that the complexity of PIS is larger than that of periodical signal but is smaller than that of surrogate data.From analysis above, we have concluded that (1) SICSNA is not a stochastic signal, and there are some periodicity in it;(2) The deterministic chaos lying in the SICSNA shows that in the sympathetic nerve system, a deterministic discipline takes effect. The chaos is very important because it plays an role in keeping the balance of automatic nerve system, adapting the outer change and maintaining the stability of the inner circumstances;(3) The long term correlation in the SICSNA and its three characteristics show that in the sympathetic there is memory behavior and self-similary, at the same time, the fractality in them probably correlates with that in the HRV;(4) Complexity analysis reveals that in the dynamical system of PIS certain mode playsimportant roles. This mode probably originates in some inner dynamical mechanisms and it maybe has effect on the product of deterministic mode in HRV.To discuss the coupling relationship between SICSNA and HRV, the four methods above are applied.The results of former four method show that (1) RRD has chaos characteristic which shows that there is deterministic relationship between dynamical systems of SICSNA and HRV;(2) Fractal characteristic lying in RRD shows that the regulation of automatic nervous system to cardiovascular function has memory behavior and long term correlation, which can help automatic nerve modulate cardiovascular system to adapt large range of changes of outer circumstances;(3) There is certain deterministic mode in the RRD, which reveals that the regulation is neither periodicity nor random, but aperiodicity.The RQA has been taken to analyze coupling relationship between RRD and HRV, PRP and RRI, PPI and RRI.The analysis results shows that (1) The original PD and PR between RRD and HRV are all larger than surrogate ones(p<0.05), while the original ER is smaller than its surrogate counterpart(p<0.05);(2) The original PD between PRP and RRI and that between PPI and RRI are all larger than surrogate ones(p<0.05), while the original ER is smaller than its surrogate counterpart(p<0.05).Our study focuses on 1CSNA, and discusses the characteristics of SICSNA and its relationship with HRV through chaos analysis, fractal analysis, complexity analysis, nonlinear coupling analysis, and gets some results. These results are critical for discovering the nonlinear characteristics of ICSNA, finding the information contained in the cardiovascular regulation of ICSNA and discussing the coupling mode between ICSNA and cardiovascular system. There is some innovation in our work:...